{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "Using KMeans to cluster data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    " \n",
    "from sklearn.datasets import make_blobs\n",
    "blobs, classes = make_blobs(500, centers=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xc14c048>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DoAwMajyIT3p+gsvt4r4f72P2rnMLE5zfJXu+I+lHvM8p/0z80+c8h9vhE4oK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\nTg5Ubsor7psKZs6MPy2YtQcxL89Zd9XKtGn2fIIx3DNtGsKdWuGPprQ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RW7wY3myHDvbx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\ngiAILhGjKQiCIAguEaMpCIIgCC75f7gzM6y9YkJqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbf8e8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(7.5, 7.5))\n",
    "rgb = np.array(['r', 'g', 'b'])\n",
    "ax.scatter(blobs[:, 0], blobs[:, 1], color=rgb[classes])\n",
    "ax.set_title(\"Blobs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
       "    n_clusters=3, n_init=10, n_jobs=1, precompute_distances='auto',\n",
       "    random_state=None, tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "kmean = KMeans(n_clusters=3)\n",
    "\n",
    "kmean.fit(blobs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-4.0278288 , -1.47161522],\n",
       "       [-7.41543262,  9.65372724],\n",
       "       [-9.20961205, -3.80781419]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmean.cluster_centers_ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xd15aef0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1NGoNZ1LOiKApCPkQQVO4I946b+Z1n0dqTiobojcQlRLF8EeHY3VYmXtoLnqN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\nTJe3zZypS9OolQmF3EOHsZh+/7jjgO++s5NXIhEdKvRqyRJ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919NPt9vUs2fjA2b79pot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DurVFTo3o8ff5zZMUR0veT22+uymZtv5tpJIqJsYNBsQUQ0QMaX84vFdG/MTIwdq8k4K1fqVl+j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\naBIREXn0/2+cG5EdU4WtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd0d7438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(7.5, 7.5))\n",
    "ax.scatter(blobs[:, 0], blobs[:, 1], color=rgb[classes])\n",
    "ax.scatter(kmean.cluster_centers_[:, 0],kmean.cluster_centers_[:, 1], marker='*', s=250,color='black', label='Centers')\n",
    "ax.set_title(\"Blobs\")\n",
    "ax.legend(loc='best')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 2, 1, 0])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmean.labels_[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 2, 1, 0])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classes[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  2.30163443,   9.50371088,   7.05130923],\n",
       "       [  0.31910166,  11.81522234,   5.92415839],\n",
       "       [  6.39025106,  15.14516351,   1.59964803],\n",
       "       [ 10.52888505,   1.22652618,  12.35407068],\n",
       "       [  0.69160906,  12.15363885,   6.10259697]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmean.transform(blobs)[:5]"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
